(290 days)
Not Found
Yes
The document explicitly states, "This device uses machine learning as part of its key functionality."
No
The device is intended for labeling, visualization, and volumetric quantification of brain structures for diagnostic purposes and reporting, not for providing therapy.
No
The device is intended for "labeling, visualization and volumetric quantification of segmentable brain structures" and the "production of a radiological report" for patients with known diagnoses. It is described as a "facilitating tool for the physicians" to identify, label, and quantify brain structure volumes. It does not state that it provides a diagnosis or aids in diagnosis, but rather processes images for reporting and analysis by a physician.
Yes
The device description explicitly states "Jazz is a Software as a Medical Device (SaMD) consisting of a software".
No, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are medical devices used to examine specimens taken from the human body (like blood, urine, tissue) to provide information about a person's health. This testing is done outside of the body (in vitro).
- Jazz's Function: Jazz processes images (MR images) of the brain, which are acquired from the body, but the processing itself is not done on a biological specimen. It's analyzing existing image data.
- Intended Use: The intended use clearly states it's for "labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images." This is image analysis, not diagnostic testing of biological samples.
Therefore, based on the provided information, Jazz falls under the category of a medical device that performs image processing and analysis, but it is not an In Vitro Diagnostic device.
No
The provided input explicitly states "Control Plan Authorized (PCCP): Not Found", indicating no PCCP was authorized for this device.
Intended Use / Indications for Use
Jazz is intended for the labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images, for patients with a known diagnosis of multiple sclerosis pipeline) and/or brain metastasis (for the metastasis pipeline), and the production of a radiological report.
Product codes
LLZ
Device Description
Jazz is a Software as a Medical Device (SaMD) consisting of a software intended to be a facilitating tool for the physicians, in the sense of a semi-automatic pipeline for the process of identifying, labeling and quantifying the volume of segmentable brain structures identified on MR images. "Semi-automatic" refers to the possibility given to the physician to correct the segmentation of the software before saving.
Mentions image processing
Yes
Mentions AI, DNN, or ML
This device uses machine learning as part of its key functionality. Networks were trained using brain images, which were fully segregated from the test set, and using a ground truth which was set using gold standard human expert opinion.
Input Imaging Modality
MR images
Anatomical Site
brain
Indicated Patient Age Range
Not Found
Intended User / Care Setting
trained professionals in hospitals, imaging centers or in image processing labs.
Description of the training set, sample size, data source, and annotation protocol
Networks were trained using brain images, which were fully segregated from the test set, and using a ground truth which was set using gold standard human expert opinion.
Description of the test set, sample size, data source, and annotation protocol
The subjects upon whom the device was tested include healthy subjects, multiple sclerosis and metastasis patients.
Summary of Performance Studies
To demonstrate the performance of Jazz, the measured volumes of the segmentable brain structures are validated for accuracy and reproducibility. In the accuracy experiments, the measured volumes are validated for accuracy against manually labeled ground truth volumes. In the reproducibility experiments, the volumes are compared on test-retest image data sets. All experiments passed the acceptance criteria. System verification tests demonstrated that the system provides the capabilities necessary to operate according to its intended use.
Experiments encompassed 344 subject datasets in total.
One accuracy experiment: voxel-wise sensitivity of at least 40%, a voxel-wise specificity of at least 95%, and a lesion-wise dice score of at least 0.5 for both the multiple sclerosis high sensitivity and high specificity models, as well as a lesion-wise true positive rate of at least 60% and a lesion-wise false negative rate of at most 40% for the high sensitivity model, as well as a lesion-wise false discovery rate of at most 50% for the high specificity model.
Another accuracy experiment: accuracy of the anatomy localization was assessed using an anatomy localization score, and the acceptance criteria for device performance was set to an anatomy localization score of 1 (best) in at least 80% of the cases, and an anatomy localization score of 6 in less than 10% of the lesions.
Another accuracy experiment: accuracy of the coregistration was assessed using a coregistration score, and the acceptance criteria for device performance was set to an average quality of the coregistration score larger than 4 (good coregistration), and the percentage of the coregistration score equaling 2 (bad coregistration) or worse smaller than 10%.
Reproducibility was tested by producing and reproducing a report using Jazz. The acceptable device performance were set to be an identical number of lesions volume and report generated in a process-reprocess experiment with Jazz.
Key Metrics
voxel-wise sensitivity of at least 40%, a voxel-wise specificity of at least 95%, and a lesion-wise dice score of at least 0.5, a lesion-wise true positive rate of at least 60% and a lesion-wise false negative rate of at most 40%, a lesion-wise false discovery rate of at most 50%.
Anatomy localization score: 1 (best) in at least 80% of the cases, and an anatomy localization score of 6 in less than 10% of the lesions.
Coregistration score: average quality larger than 4 (good coregistration), and the percentage equaling 2 (bad coregistration) or worse smaller than 10%.
Predicate Device(s)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which consists of the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" in blue, and then the word "ADMINISTRATION" in a smaller font size below.
AI Medical AG % Christian Federau CEO Goldhaldenstr 22a Zollikon, Zuerich CH 8702 SWITZERLAND
September 22, 2023
Re: K223659
Trade/Device Name: Jazz Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: August 22, 2023 Received: August 25, 2023
Dear Christian Federau:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see
1
https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Jessica Lamb
Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Ouality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K223659
Device Name Jazz
Indications for Use (Describe)
Jazz is intended for the labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images, for patients with a known diagnosis of multiple sclerosis pipeline) and/or brain metastasis (for the metastasis pipeline), and the production of a radiological report.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| ☑ Prescription Use (Part 21 CFR 801 Subpart D) | ☐ Over-The-Counter Use (21 CFR 801 Subpart C) |
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Image /page/3/Picture/0 description: The image shows the logo for AI medical. The logo consists of a blue circle with the letters "AI" in white inside the circle. To the right of the circle, the word "medical" is written in blue. The logo is simple and modern, and it is likely used to represent a company that specializes in artificial intelligence for medical applications.
K223659 510(k) Summary
5.1 Submitter
| Name | Al Medical AG |
|---|---|
| Address | Goldhaldenstr 22a |
| 8702 Zollikon | |
| Switzerland | |
| Contact Persion | Christian Federau |
| Telephone Number | +41 78 8402880 |
| christian@ai-medical.ch | |
| Date prepared | 15 Aug 2023 |
5.2 Device
| Device Trade Name | Jazz |
|---|---|
| Common Name | Medical Image Processing Software |
| Classification Name | System, Image processing, Radiological |
| Number | 892.2050 |
| Product Code | QIH (LLZ) |
| Classification Panel | Radiology |
5.3 Predicate Device
| 510(k) Number | K192130 |
|---|---|
| Device Name | icobrain |
| Manufacturer | icometrix NV |
| Tervuursesteenweg 244 | |
| B-3001 Leuven Belgium | |
| Classification Name | System, Image processing, Radiological |
| Number | 892.2050 |
| Product Code | LLZ |
| Classification Panel | Radiology |
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Image /page/4/Picture/0 description: The image shows the logo for AI Medical. The logo consists of the letters "AI" inside of a circle, with the word "medical" to the right of the circle. The logo is in a dark blue color.
5.4 Device Description
Jazz is a Software as a Medical Device (SaMD) consisting of a software intended to be a facilitating tool for the physicians, in the sense of a semi-automatic pipeline for the process of identifying, labeling and quantifying the volume of segmentable brain structures identified on MR images. "Semi-automatic" refers to the possibility given to the physician to correct the segmentation of the software before saving.
The following flowchart illustrates the overall architecture of Jazz.
Image /page/4/Figure/4 description: The image shows a diagram of a medical imaging process. The process consists of four steps: Input Images (DICOMS), Preprocessing (image coregistration, contrast recognition, abnormalities pre-annotation), Neuroradiological Confirmation, and Report Generation (txt, pdf) Summaries (DICOMS). The steps are numbered 1-4 and are connected by arrows.
The input images must be MR images. During pre-processing, images get coregistered, contrast get recognized, and the abnormalities can get optionally pre-annotated. Several algorithms for the pre-annotation of the abnormalities can be used during the preprocessing. In case a pre-annotation get used, the physician can evaluate the pre-annotation of the different algorithms, and select the one he judges the best. He might also decide to use none of them. In all cases, the physician has to review the annotation.
In other words, the use of a pre-annotation of the abnormalities by the physician is facultative, and he has the choice to:
-
- use a pre-annotation of abnormalities as they are, if he considers it is adequate after reviewing them
-
- use a pre-annotation of abnormalities but correct them, if he considers that corrections are necessary adequate after reviewing them
-
- don't use a pre-annotation of abnormalities at all, and annotate the anomalities manually himself
Finally, the physician output is used to compute an electronic report, which again can be annotated by the physician if he considers it necessary. The electronic report and images summaries get saved in the format choosen by the user (txt, pdf, DICOMs). Thus, the physician remains fully in control of the output.
ર્સ
જિલ્લાના ગુજરાત રાજ્યના અભિન્યાન અભિન્યાન અભિન્યાન કરતાં જિલ્લાના ગામનાં લોકોનો મુખ્ય વ્યવસાય ખેતી, ખેતમજૂરી તેમ જ પશુપાલન છે. આ ગામનાં મુખ્યત્વે ખેત-ઉત્પાદની ખેતી, ખેત Indication of Use
Jazz is intended for the labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images, for patients with a known diagnosis of multiple sclerosis (for the multiple sclerosis pipeline) and/or brain metastasis (for the metastasis pipeline), and the production of a radiological report.
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Image /page/5/Picture/0 description: The image shows the logo for AI Medical. The logo consists of a dark blue circle with the letters "AI" in white inside the circle. To the right of the circle, the word "medical" is written in a smaller, sans-serif font, also in dark blue. The logo is simple and modern, with a focus on the company's name.
5.6 Comparison of Technological Characteristics with the Predicate Device
Jazz, the device subject to this submission and IcoBrain, the predicate device (K192130) have an identical classification.
| Device | Jazz | IcoBrain |
|---|---|---|
| Regulation Number | 21 CFR 892.2050 | 21 CFR 892.2050 |
| Device Classification | ||
| Name | System, Image processing, Radiological | System, Image processing, Radiological |
| Product Code | QIH (LLZ) | LLZ |
| Regulatory Class | II | II |
| Intended Use / | ||
| Indications for use | Jazz is intended for the labeling, visualization and volumetric | |
| quantification of segmentable brain | ||
| structures from a set of MR images, for | ||
| patients with a known diagnosis of | ||
| multiple sclerosis (for the multiple | ||
| sclerosis pipeline) and/or brain | ||
| metastasis (for the metastasis pipeline), | ||
| and the production of a radiological | ||
| report. | icobrain is intended for automatic | |
| labeling, visualization and volumetric | ||
| quantification of segmentable brain | ||
| structures from a set of MR or NCCT | ||
| images. This software is intended to | ||
| automate the current manual process of | ||
| identifying, labeling and quantifying the | ||
| volume of segmentable brain structures | ||
| identified on MR or NCCT images. |
icobrain consists of two distinct image
processing pipelines: icobrain cross and
icobrain long.
• icobrain cross is intended to provide
volumes from MR or NCCT images
acquired at a single time point.
• icobrain long is intended to provide
changes in volumes between two MR
images that were acquired on the same
scanner, with the same image acquisition
protocol and with same contrast at two
different timepoints.
The results of icobrain cross cannot be
compared with the results of icobrain
long. |
Table 1. Comparison with predicate device
Device and predicate device are software for identifying the volumes of brain structures, labeling and visualization. Both devices take 3D MR images of the brain as input and generate an electronic report with similar quantitative information.
Both devices are DICOM compatible, operate on off-the-shelf hardware and are used by trained professionals in hospitals, imaging centers or in image processing labs.
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Image /page/6/Picture/0 description: The image shows the logo for AI medical. The logo consists of a dark blue circle with the letters "AI" in white inside the circle. To the right of the circle, the word "medical" is written in dark blue. The logo is simple and modern, and it is likely used to represent a company that specializes in artificial intelligence for medical applications.
The Jazz software includes a verification and correction step by a trained physician before the report is produced. Icobrain produces the report automatically.
5.7 Performance Data
To demonstrate the performance of Jazz, the measured volumes of the segmentable brain structures are validated for accuracy and reproducibility. In the accuracy experiments, the measured volumes are validated for accuracy against manually labeled ground truth volumes. In the reproducibility experiments, the volumes are compared on test-retest image data sets. A literature review has been performed to set relevant acceptance criteria for each type of experiment. All experiments passed the acceptance criteria.
This device uses machine learning as part of its key functionality. Networks were trained using brain images, which were fully segregated from the test set, and using a ground truth which was set using gold standard human expert opinion.
The experiments encompassed 344 subject datasets in total. The subjects upon whom the device was tested include healthy subjects, multiple sclerosis and metastasis patients.
In one accuracy experiment, the acceptance criteria for device performance were set to be a voxel-wise sensitivity of at least 40%, a voxel-wise specificity of at least 95%, and a lesion-wise dice score of at least 0.5 for both the multiple sclerosis high sensitivity and high specificity models, as well as a lesion-wise true positive rate of at least 60% and a lesion-wise false negative rate of at most 40% for the high sensitivity model, as well as a lesion-wise false discovery rate of at most 50% for the high specificity model.
In another accuracy experiment, the accuracy of the anatomy localization was assessed using an anatomy localization score, and the acceptance criteria for device performance was set to an anatomy localization score of 1 (best) in at least 80% of the cases, and an anatomy localization score of 6 in less than 10% of the lesions.
In another accuracy experiment, the accuracy of the coregistration was assessed using a coregistration score, and the acceptance criteria for device performance was set to an average quality of the coregistration score larger than 4 (good coregistration), and the percentage of the coregistration score equaling 2 (bad coregistration) or worse smaller than 10%.
Reproducibility was tested by producing and reproducing a report using Jazz. The acceptable device performance were set to be an identical number of lesions volume and report generated in a process-reprocess experiment with Jazz.
All experiments passed the acceptance criteria. In addition, system verification tests demonstrated that the system provides the capabilities necessary to operate according to its intended use.
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Image /page/7/Picture/0 description: The image contains the logo for AI Medical. The logo consists of the letters "AI" inside of a blue circle. To the right of the circle, the word "medical" is written in a smaller font size.
5.8 Conclusions
Jazz is a labeling, visualization and segmentation software which has similar intended use and indications for use statement as the predicate device. This 510(k) submission includes information on Jazz technological characteristics, as well as performance data and velidation activities demonstrating that Jazz is as safe and effective as the predicate, and does not raise different questions of safety and effectiveness.
| Declarations: | • This summary includes only information that is also covered in the body of the 510(k) • This summary does not contain any puffery or unsubstantiated labeling claims. • This summary does not contain any raw data, i.e., contains only summary data. • This summary does not contain any trade secret or confidential commercial information. • This summary does not contain any patient identification information. |
|---|---|
| --------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
This document is reviewed and approved by Christian Federau, CEO of Al Medical, based on the present data and information.